Patient perception of nursing care received is an important quality indicator. However, there is lack of a reliable and valid instrument to measure patient perceptions of nursing care in the hospital setting. The Patient-Perceived Nursing Care Quality (PNCQ) questionnaire was developed through extensive literature review, content analysis of published instruments, patient interviews, content validation from patients and health care professionals, pretests, and a pilot study. Three dimensions underling perceived nursing care quality are proposed: care of perceived needs, perceived professional competency in managing care, and care of physical environment. Two scales measure patient perceptions regarding the consistency of nursing care quality: quality (poor, fair, good, and very good) and frequency (once or twice, some of the time, most of the time, and all of the time). The purpose of the study is to examine the psychometric properties of the PNCQ. Specific aims include (a) to examine internal consistency and test-retest reliability and (b) to examine construct validity, criterion-related validity, discriminance validity, and convergent and discriminant validity. A cross-sectional design with repeated measures on a subsample of patients will be used. The study sample will include adult patients who will be discharged to home from eight medical or surgical units of two acute care hospitals in one large Midwestern city; 75 patients who meet inclusion criteria will be randomly selected from each unit (n = 600). Consenting patients will be called 5 to 26 days after discharge. A subsample of 12 patients from each unit (n= 96) will be reinterviewed in 2 weeks to examine stability. To examine reliability, the individual patient will be the unit of analysis. To examine validity, both the individual patient and the study unit will be the unit of analysis. Cronbach's alpha and intraclass correlation coefficients will be used to analyze internal consistency and test-retest reliability. Exploratory and confirmatory factor analyses, structural equation modeling, one-way analysis of variance, Chi-square, Loglinear model, and Pearson correlation will be used to evaluate various types of validity.